Hands-On Automobile Learning With Scikit-Learn Too Tensorflow: Concepts, Tools, Together With Techniques To Make Intelligent Systems
Through a serial of recent breakthroughs, deep learning has boosted the entire champaign of auto learning. Now, fifty-fifty programmers who know close to nix almost this engineering science can purpose uncomplicated, efficient tools to implement programs capable of learning from data. This practical book shows you lot how.
By using concrete examples, minimal theory, together with 2 product-cook Python frameworks―scikit-larn and TensorFlow―author Aurélien Géron helps you lot make an intuitive agreement of the concepts together with tools for building intelligent systems. You’ll acquire a reach of techniques, starting alongside uncomplicated linear regression as well as progressing to deep neural networks. With exercises inwards each chapter to help you use what you lot’ve learned, all you involve is programming experience to go started.
- Explore the machine learning landscape, peculiarly neural nets
- Use scikit-acquire to rail an example automobile-learning project cease-to-terminate
- Explore several preparation models, including support vector machines, conclusion trees, random forests, too ensemble methods
- Use the TensorFlow library to build and prepare neural nets
- Dive into neural cyberspace architectures, including convolutional nets, recurrent nets, and deep reinforcement learning
- Learn techniques for training and scaling deep neural nets
- Apply practical code examples without acquiring excessive auto learning theory or algorithm details
